The Alliance of Bioversity International and CIAT delivers research-based solutions that harness agricultural biodiversity and sustainably transform food systems to improve people\u2019s lives. Alliance solutions address the global crises of malnutrition, climate change, biodiversity loss, and environmental degradation.
\nThe Alliance works with local, national and multinational partners across Latin America and the Caribbean, Asia and Africa, and with the public and private sectors. The Alliance is part of CGIAR, a global research partnership for a food-secure future, dedicated to reducing poverty, enhancing food and nutrition security, and improving natural resources and ecosystem services.
\nAbout the position
\nThe Senior Machine Learning Operations (MLOps) Associate will support the development, deployment, and maintenance of ML models and infrastructure within the Artemis project. This role focuses on assisting in ML pipeline development, automating workflows, managing model performance in production, and ensuring smooth integration into research and application environments. The Senior associate will work closely with the engineering and product development teams to support scalable, reliable, and well-documented ML operations.
\nKey duties & responsibilities
\nModel development:<\/p>\n
\u00a0Oversee training and evaluation of robust, high-accurate models for crop phenotyping.
\n\u00a0Perform data preprocessing and feature engineering for model training.
\n\u00a0Conduct basic hyperparameter tuning and model validation experiments.<\/p>\n
Machine Learning pipeline development and maintenance:<\/p>\n
\u00a0Develop and maintain ML pipelines for training, validation, and deployment.
\n\u00a0Automate workflows for data preprocessing, model retraining, and evaluation.
\n\u00a0Ensure model artifacts are properly versioned and documented.<\/p>\n
Model deployment and monitoring:<\/p>\n
\u00a0Support the deployment of ML models in production environments.
\n\u00a0Set up monitoring tools to track model performance and detect drift.
\n\u00a0Optimize inference speed and resource usage for improved efficiency.<\/p>\n
Infrastructure and CI\/CD for ML<\/p>\n
\u00a0Setup and maintain cloud-based and on-premise ML infrastructure.
\n\u00a0Support the implementation of CI\/CD pipelines for automated model updates and deployment.<\/p>\n
\u00a0Work closely with software engineers, user research experts, and product teams to integrate ML models into applications.
\n\u00a0Perform model testing and validating outputs for usability and accuracy.
\n\u200bProvide technical support for model-related issues in production.<\/p>\n
Requirements<\/p>\n
\u00a0Master\u2019s degree in Computer Science, Engineering, or a related field.
\n\u00a03+ years of experience in machine learning, data engineering, or related domains
\n\u00a0Proficient in data preprocessing, model training, evaluation, and optimization
\n\u00a0Experienced in deploying models to production environments and monitoring their performance.
\n\u00a0Proficiency in Python and machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
\n\u00a0Basic experience with cloud platforms (GCP, AWS, Azure).
\n\u00a0Familiarity with ML pipeline orchestration tools (e.g., Kubeflow, MLflow, Airflow).
\n\u00a0Understanding of CI\/CD for ML deployment.
\n\u00a0Strong problem-solving skills and attention to detail.
\n\u00a0Excellent communication and interpersonal skills.
\n\u00a0Ability to work independently and as part of a team.<\/p>\n
Terms of employment
\nThis position is a\u00a0nationally\u00a0recruited position based in Arusha, Tanzania\u00a0.\u00a0The initial contract will be for\u00a01 year\u00a0subject to a probation period of\u00a03\u00a0months and is renewable depending on performance and availability of resources.
\nThis position is graded at\u00a0BG07\u00a0,\u00a0level, with a minimum basic salary of TSZ\u00a03,929,704 in a scale of BG01 to BG14 (BG14 being the highest level according to the Alliance job classification framework policy). We offer a competitive salary and excellent benefits including but not limited to insurance, retirement plan, staff training and development, paid time off and flexible working arrangements.
\nThe Alliance Bioversity-CIAT is committed to fair, safe, and inclusive workplaces. We believe that diversity powers our innovation, contributes to our excellence, and is critical for our mission. Recruiting and mentoring staff to create an inclusive organization that reflects our global character is a priority. We encourage applicants from all cultures, races, colors, religions, sexes, national or regional origins, ages, disability statuses, sexual orientations, marital status, and gender identities. Female candidates are strongly encouraged to apply
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